Quantum theory is the area of study that focuses on trying to explain the phenomenon of energy and matter on the quantum level.
Add that to computing applications, and we get Quantum computing, which uses the principles of quantum theory to develop computer technologies. This in itself is a subfield of quantum information science; quantum computing is a field of study that encompasses quantum cryptography and quantum communication.
A quantum computer is expected to have computing capabilities far greater than those of abacus and a modern-day supercomputer. Following the laws of physics, quantum computers will have enormous power, as it will have the capability to be in multiple states at the same time and perform tasks using all possible permutations simultaneously.
All computing devices rely on the basic ability to store and process information. Current computers have the ability to store information in the form of bits which can hold binary values of 1 and 0. Quantum computers, on the other hand, store information in the form of quantum bits or qubits.
Quantum computing is a major trend in the computer science industry today. The possible applications of quantum computing are endless. Here are a few applications of quantum computing from the vast possibilities.
Applications of quantum computing
If recognized in its early stages, some forms of cancer are treatable. This treatment can include various methods such as surgery, chemotherapy, and radiation therapy. A major factor in treating cancer by radiation therapy is beam optimization. Radiation given to a patient kills the cells in the region, which it affects.
Often, along with the cancer cells, some surrounding part of the healthy cells, too, are destroyed. Various methods of radiation have been developed in the past decade that use our classical computers. However, in 2015, the researchers at the Roswell Park Cancer Institute proposed a new way to optimize the radiation beams that uses quantum annealing computers.
Traffic is one of the leading issues that we face today. Google has been trying to address the issue by suggesting alternate routes and by highlighting the places of moderate and high traffic. This, however, does not address the problem of traffic on the roads. In 2017, Volkswagen tried to address the issue of traffic by tackling the traffic itself.
They used the QUBO-Quadratic Unconstraint Binary Optimization technique along with the quantum annealing computers to find the optimal route for a certain number of cars in addition to all the possible routes in consideration. Till now, they have tested about 10000 taxis in Beijing to prove how this method optimizes traffic faster than what the classical computers can.
Knowing which assets to invest in and which asset to divest is a challenge that cannot be solved using modern day computing. Ensuring that your portfolio is healthy will be the difference in the capital you attain in the future.
Portfolio optimization deals with selecting the best asset to invest in, which balances the risk with the expected returns. A tough problem to solve for conventional computers, but quantum annealing can help answer these in a jiffy.
Molecule simulation helps us understand the structure of molecules and the nature of their interaction with one another. Even though classical computers are able to simulate molecules, they have limitations on the complexity in a simulation that they can handle.
Quantum computers are able to overcome this limitation. Till date, quantum computers have been able to simulate small molecules like beryllium hydride (BeH2). Even if this looks small now, the fact that a 7-qubit chip simulated this molecule holds significance as had there been more qubits at our disposal, it would’ve been possible to simulate bigger molecules. The processing capabilities of a quantum computer increase with an increase in the number of qubits.
Artificial intelligence is the science that allows machines to simulate human behavior. Researchers have been trying to develop AI, which is more human-like. Machine learning and neural networks are the underlying technologies behind AI. Neural networks use data sets based on matrices for computational purposes, which uses matrix algebra.
Quantum computing itself works in such a way that often matrices are used to determine the states of the qubits. So essentially, any computational process performed on the neural networks would be similar to applying transformational quantum gates on qubits (a quantum gate is a basic circuit operating on a small number of qubits). This makes quantum computers a perfect fit to implement AI.
We have all faced a time when we see a sunny forecast, and as soon as we step out, it starts pouring. Weather forecasts are never 100% accurate. In 2017, a researcher from Russia published a paper proposing the possibility of quantum computers predicting the weather more accurately as compared to classical computers.
There are certain limitations that our current computers face in predicting all intricate weather changes. A major issue with predicting the weather correctly is the involvement of a large amount of data. With the help of the Dynamic Quantum Clustering (DQC) methodology, quantum computers are expected to speed up the data processing to give us more accurate weather forecasts.
It sure is annoying when we want to read some article online, but we see it is surrounded by advertisements all over. Often, these ads don’t even seem relevant. Recruit Communications has come up with the solution to one of these – relevancy of ads. In their research, they have explained how companies can take the help of quantum annealing to reach their audience with relevant ads so as to increase the CTR (Click Through Rate).
Currently, the field of quantum computing is still in its very early stages, and a vast amount of research is yet to go into it. The current hardware and compatible software haven’t reached its full potential. It sure is clear that quantum computing is going to find applications in many more fields. Let’s wait and see what it has in store for us in the future.